Biomechanical implications of walking with indigenous footwear

Objectives This study investigates biomechanical implications of walking with indigenous “Kolhapuri” footwear compared to barefoot walking among a population of South Indians. Materials and methods Ten healthy adults from South India walked barefoot and indigenously shod at voluntary speed on an artificial substrate. The experiment was repeated outside, on a natural substrate. Data were collected from (1) a heel‐mounted 3D‐accelerometer recording peak impact at heel contact, (2) an ankle‐mounted 3D‐goniometer (plantar/dorsiflexion and inversion/eversion), and (3) sEMG electrodes at the m. tibialis anterior and the m. gastrocnemius medialis. Results Data show that the effect of indigenous footwear on the measured variables, compared to barefoot walking, is relatively small and consistent between substrates (even though subjects walked faster on the natural substrate). Walking barefoot, compared to shod walking yields higher impact accelerations, but the differences are small and only significant for the artificial substrate. The main rotations of the ankle joint are mostly similar between conditions. Only the shod condition shows a faster ankle rotation over the rapid eversion motion on the natural substrate. Maximal dorsiflexion in late stance differs between the footwear conditions on an artificial substrate, with the shod condition involving a less dorsiflexed ankle, and the plantar flexion at toe‐off is more extreme when shod. Overall the activity pattern of the external foot muscles is similar. Discussion The indigenous footwear studied (Kolhapuri) seems to alter foot biomechanics only in a subtle way. While offering some degree of protection, walking in this type of footwear resembles barefoot gait and this type of indigenous footwear might be considered “minimal”

User Identification Using Gait Patterns on UbiFloorII

This paper presents a system of identifying individuals by their gait patterns. We take into account various distinguishable features that can be extracted from a user’s gait and then divide them into two classes: walking pattern and stepping pattern. The conditions we assume are that our target environments are domestic areas, the number of users is smaller than 10, and all users ambulate with bare feet considering the everyday lifestyle of the Korean home. Under these conditions, we have developed a system that identifies individuals’ gait patterns using our biometric sensor, UbiFloorII. We have created UbiFloorII to collect walking samples and created software modules to extract the user’s gait pattern. To identify the users based on the gait patterns extracted from walking samples over UbiFloorII, we have deployed multilayer perceptron network, a feedforward artificial neural network model. The results show that both walking pattern and stepping pattern extracted from users’ gait over the UbiFloorII are distinguishable enough to identify the users and that fusing two classifiers at the matching score level improves the recognition accuracy. Therefore, our proposed system may provide unobtrusive and automatic user identification methods in ubiquitous computing environments, particularly in domestic areas

Weight-bearing cone beam CT scans in the foot and ankle

The 3D anatomical complexity of the foot and ankle and the importance of weight-bearing in diagnosis have required the combination of conventional radiographs and medical CT. Conventional plain radiographs (XR) have demonstrated substantial limitations such as perspective, rotational and fan distortion, as well as poor reproducibility of radiographic installations. Conventional CT produces high levels of radiation exposure and does not offer weight-bearing capabilities. The literature investigating biometrics based on 2D XR has inherent limitations due to the technology itself and thereby can focus only on whether measurements are reproducible, when the real question is whether the radiographs are. Low dose weight-bearing cone beam CT (WBCT) combines 3D and weight-bearing as well as 'built in' reliability validated through industry-standardized processes during production and clinical use (quality assurance testing). Research is accumulating to validate measurements based on traditional 2D techniques, and new 3D biometrics are being described and tested. Time- and cost-efficient use in medical imaging will require the use of automatic measurements. Merging WBCT and clinical data will offer new perspectives in terms of research with the help of modern data analysis techniques

Biometric walk recognizer. Research and results on wearable sensor-based gait recognition

Gait is a biometric trait that can allow user authentication, though being classified as a "soft" one due to a certain lack in permanence, and to sensibility to specific conditions. The earliest research relies on computer vision-based approaches, especially applied in video surveillance. More recently, the spread of wearable sensors, especially those embedded in mobile devices, which are able to capture the dynamics of the walking pattern through simpler 1D signals, has spurred a different research line. This capture modality can avoid some problems related to computer vision-based techniques, but suffers from specific limitations. Related research is still in a less advanced phase with respect to other biometric traits. However, the promising results achieved so far, the increasing accuracy of sensors, the ubiquitous presence of mobile devices, and the low cost of related techniques, make this biometrics attractive and suggest to continue the investigations in this field. The first Chapters of this thesis deal with an introduction to biometrics, and more specifically to gait trait. A comprehensive review of technologies, approaches and strategies exploited by gait recognition proposals in the state-of-the-art is also provided. After such introduction, the contributions of this work are presented in details. Summarizing, it improves preceding result achieved during my Master Degree in Computer Science course of Biometrics and extended in my following Master Degree Thesis. The research deals with different strategies, including preprocessing and recognition techniques, applied to the gait biometrics, in order to allow both an automatic recognition and an improvement of the system accuracy

Analysis of Affective State as Covariate in Human Gait Identification

There is an increased interest in the need for a noninvasive and nonintrusive biometric identification and recognition system such as Automatic Gait Identification (AGI) due to the rise in crime rates in the US, physical assaults, and global terrorism in public places. AGI, a biometric system based on human gait, can recognize people from a distance and current literature shows that AGI has a 95.75% success rate in a closely controlled laboratory environment. Also, this success rate does not take into consideration the effect of covariate factors such as affective state (mood state); and literature shows that there is a lack of understanding of the effect of affective state on gait biometrics. The purpose of this study was to determine the percent success rate of AGI in an uncontrolled outdoor environment with affective state as the main variable. Affective state was measured using the Profile of Mood State (POMS) scales. Other covariate factors such as footwear or clothes were not considered in this study. The theoretical framework that grounded this study was Murray\u27s theory of total walking cycle. This study included the gait signature of 24 participants from a population of 62 individuals, sampled based on simple random sampling. This quantitative research used empirical methods and a Fourier Series Analysis. Results showed that AGI has a 75% percent success rate in an uncontrolled outdoor environment with affective state. This study contributes to social change by enhancing an understanding of the effect of affective state on gait biometrics for positive identification during and after a crime such as bank robbery when the use of facial identification from a surveillance camera is either not clear or not possible. This may also be used in other countries to detect suicide bombers from a distance